Quantitative Portfolio Optimization
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Quantitative Portfolio Optimization
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Author : Miquel Noguer Alonso
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22
Quantitative Portfolio Optimization written by Miquel Noguer Alonso and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Business & Economics categories.
Expert guidance on implementing quantitative portfolio optimization techniques In Quantitative Portfolio Optimization: Theory and Practice, renowned financial practitioner Miquel Noguer, alongside physicists Alberto Bueno Guerrero and Julian Antolin Camarena, who possess excellent knowledge in finance, delve into advanced mathematical techniques for portfolio optimization. The book covers a range of topics including mean-variance optimization, the Black-Litterman Model, risk parity and hierarchical risk parity, factor investing, methods based on moments, and robust optimization as well as machine learning and reinforcement technique. These techniques enable readers to develop a systematic, objective, and repeatable approach to investment decision-making, particularly in complex financial markets. Readers will gain insights into the associated mathematical models, statistical analyses, and computational algorithms for each method, allowing them to put these techniques into practice and identify the best possible mix of assets to maximize returns while minimizing risk. Topics explored in this book include: Specific drivers of return across asset classes Personal risk tolerance and it#s impact on ideal asses allocation The importance of weekly and monthly variance in the returns of specific securities Serving as a blueprint for solving portfolio optimization problems, Quantitative Portfolio Optimization: Theory and Practice is an essential resource for finance practitioners and individual investors It helps them stay on the cutting edge of modern portfolio theory and achieve the best returns on investments for themselves, their clients, and their organizations.
Quantitative Portfolio Optimisation Asset Allocation And Risk Management
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Author : M. Rasmussen
language : en
Publisher: Springer
Release Date : 2002-12-13
Quantitative Portfolio Optimisation Asset Allocation And Risk Management written by M. Rasmussen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-12-13 with Business & Economics categories.
Targeted towards institutional asset managers in general and chief investment officers, portfolio managers and risk managers in particular, this practical book serves as a comprehensive guide to quantitative portfolio optimization, asset allocation and risk management. Providing an accessible yet rigorous approach to investment management, it gradually introduces ever more advanced quantitative tools for these areas. Using extensive examples, this book guides the reader from basic return and risk analysis, all the way through to portfolio optimization and risk characterization, and finally on to fully fledged quantitative asset allocation and risk management. It employs such tools as enhanced modern portfolio theory using Monte Carlo simulation and advanced return distribution analysis, analysis of marginal contributions to absolute and active portfolio risk, Value-at-Risk and Extreme Value Theory. All this is performed within the same conceptual, theoretical and empirical framework, providing a self-contained, comprehensive reading experience with a strongly practical aim.
Modern Portfolio Optimization With Nuopttm S Plus And S Bayestm
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Author : Bernd Scherer
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-05
Modern Portfolio Optimization With Nuopttm S Plus And S Bayestm written by Bernd Scherer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-05 with Business & Economics categories.
In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.
Quantitative Portfolio Management
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Author : Pierre Brugière
language : en
Publisher: Springer Nature
Release Date : 2020-03-28
Quantitative Portfolio Management written by Pierre Brugière and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Mathematics categories.
This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage opportunities are extensively used and enable the translation of all the mathematical concepts in an easily interpretable way. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and intrinsic approaches for statistical methods, leading to unusually short and elegant proofs. The statistical methods concern both parametric and non-parametric estimators and, to estimate the factors of a model, principal component analysis is explained. The presented Python code and web scraping techniques also make it possible to test the presented concepts on market data. This book will be useful for teaching Masters students and for professionals in asset management, and will be of interest to academics who want to explore a field in which they are not specialists. The ideal pre-requisites consist of undergraduate probability and statistics and a familiarity with linear algebra and matrix manipulation. Those who want to run the code will have to install Python on their pc, or alternatively can use Google Colab on the cloud. Professionals will need to have a quantitative background, being either portfolio managers or risk managers, or potentially quants wanting to double check their understanding of the subject.
Quantitative Equity Portfolio Management
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Author : Edward E. Qian
language : en
Publisher: CRC Press
Release Date : 2007-05-11
Quantitative Equity Portfolio Management written by Edward E. Qian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-11 with Business & Economics categories.
Quantitative equity portfolio management combines theories and advanced techniques from several disciplines, including financial economics, accounting, mathematics, and operational research. While many texts are devoted to these disciplines, few deal with quantitative equity investing in a systematic and mathematical framework that is suitable for
Quantitative Equity Portfolio Management
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Author : Ludwig B. Chincarini
language : en
Publisher: McGraw Hill Professional
Release Date : 2010-08-18
Quantitative Equity Portfolio Management written by Ludwig B. Chincarini and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-18 with Business & Economics categories.
Quantitative Equity Portfolio Management brings the orderly structure of fundamental asset management to the often-chaotic world of active equity management. Straightforward and accessible, it provides you with nuts-and-bolts details for selecting and aggregating factors, building a risk model, and much more.
Quantitative Methods For Portfolio Analysis
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Author : T. Kariya
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Quantitative Methods For Portfolio Analysis written by T. Kariya and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
Quantitative Methods for Portfolio Analysis provides practical models and methods for the quantitative analysis of financial asset prices, construction of various portfolios, and computer-assisted trading systems. In particular, this book is required reading for: (1) `Quants' (quantitatively-inclined analysts) in financial industries; (2) financial engineers in investment banks, securities companies, derivative-trading companies, software houses, etc., who are developing portfolio trading systems; (3) graduate students and specialists in the areas of finance, business, economics, statistics, financial engineering; and (4) investors who are interested in Japanese financial markets. Throughout the book the emphasis is placed on the originality and usefulness of models and methods for the construction of portfolios and investment decision making, and examples are provided to demonstrate, with practical analysis, models for Japanese financial markets.
Robust Portfolio Optimization And Management
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Author : Frank J. Fabozzi
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-27
Robust Portfolio Optimization And Management written by Frank J. Fabozzi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-27 with Business & Economics categories.
Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University
Machine Learning For Asset Managers
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Author : Marcos M. López de Prado
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-22
Machine Learning For Asset Managers written by Marcos M. López de Prado and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with Business & Economics categories.
Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.